A regional unmanned aerial vehicle prevention and control method and device based on distributed multi-station cooperation

Abstract

The application discloses a regional unmanned aerial vehicle prevention and control method and device based on distributed multi-station cooperation, and the method comprises the following steps: acquiring regional unmanned aerial vehicle prevention and control information; the regional unmanned aerial vehicle prevention and control information comprises prior information, an unmanned aerial vehicle prevention and control region and the number of distributed unmanned aerial vehicle prevention and control stations; the prior information comprises the equivalent baseband channel fading coefficient of the distributed unmanned aerial vehicle prevention and control station, the equivalent baseband complex signal of the distributed unmanned aerial vehicle prevention and control station and the equivalent baseband noise of the distributed unmanned aerial vehicle prevention and control station; the prior information is processed to obtain an unmanned aerial vehicle position information estimation value; the unmanned aerial vehicle position information estimation value comprises a direction estimation value of the unmanned aerial vehicle position information and a coordinate estimation value of the unmanned aerial vehicle position information; the unmanned aerial vehicle position information estimation value is processed to obtain a regional unmanned aerial vehicle prevention and control result. The distributed unmanned aerial vehicle prevention and control station deploys multiple unmanned aerial vehicle prevention and control stations in a control region, so that the illegal unmanned aerial vehicles in the control region are counteracted.

Description

Technical Field

[0001] This invention relates to the field of drone control technology, and in particular to a regional drone control method and device based on distributed multi-station collaboration. Background Technology

[0002] The UAV control station involved in this patent application mainly has target positioning and target jamming functions. The target positioning function is mainly achieved through radio wave direction finding based on a multi-antenna array; the target jamming function is mainly achieved through interference with the telemetry and control link and the satellite navigation link.

[0003] Communication between low-cost UAVs and ground control stations is primarily achieved through omnidirectional antennas. As long as the power of the UAV telemetry and control link signal received by the UAV control station is above the receiver sensitivity, the UAV's orientation angle can be determined using multi-antenna direction-finding algorithms (e.g., Multiple Signal Classification (MUSIC) algorithm, Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm). After positioning is completed, the interference signal emitted by the UAV control station enters the UAV telemetry and control link receiving module or the satellite navigation link receiving module, which can reduce the signal-to-noise ratio (SNR) of the telemetry and control link or satellite navigation link receiver. When the SNR is lower than the demodulation threshold, the UAV telemetry and control link or satellite navigation link can be effectively blocked.

[0004] High-end UAVs and ground control stations are equipped with high-gain directional antennas or even phased array antennas. The telemetry and control link between them uses directional narrow-beam transmission to improve link gain and received signal quality. If the UAV control station is within the narrow-beam coverage area between the UAV and the ground control station, it can effectively locate and jam the target. When the control station is located between the UAV and the ground station, the UAV's transmitted signal enters the control station along its main lobe (the direction of maximum signal strength). The control station can effectively locate the UAV using direction-finding algorithms and then transmit jamming signals along the UAV's main lobe direction to effectively interfere with the UAV's telemetry and control link receiver. Of course, since the main lobe of the satellite navigation link signal faces space, the jamming effect of the UAV control station's jamming signal entering the satellite navigation link receiver from different directions is not significantly different. When the control station is within the extended coverage area of ​​the UAV's beam, the UAV's transmitted signal enters the control station along its main lobe. The control station can effectively locate the UAV using direction-finding algorithms and then transmit jamming signals along the UAV's main lobe direction to effectively interfere with the UAV's telemetry and control link receiver. If the UAV control station is outside the main beam coverage area between the UAV and the ground control station, it cannot effectively locate and jam the target. When the UAV transmits a signal along the back lobe (the direction of least signal strength) into the control station, the received signal is very weak and likely does not reach the receiver's sensitivity, making effective signal reception impossible. Even if the sensitivity threshold is exceeded, the low signal-to-noise ratio will affect the accuracy of the direction-finding algorithm, making accurate determination of the UAV's position impossible. During the jamming phase, even with prior information about the UAV's position, the jamming effect achieved by the jamming signal transmitted by the control station along the back lobe direction into the UAV telemetry and control link receiver is very limited. Due to the attenuation effect of the back lobe on the jamming signal, effectively blocking the telemetry and control link signal requires transmitting a jamming signal with extremely high power, which places high demands on the power amplifier and RF link capabilities of the control station, making it difficult to achieve. Even if achieved, it would cause significant spectrum pollution to the electromagnetic field over a wide area, subjecting it to policy constraints. Furthermore, since accurate information about the drone's location is not available in practice, the main lobe of the satellite navigation link interference signal emitted by the drone control station is not aligned with the drone, which weakens the interference signal strength entering the drone's satellite navigation link and reduces the interference radius of the satellite navigation link.

[0005] Direction finding and positioning of UAVs is achieved through signals transmitted from the UAV to the ground station, not signals transmitted from the ground station to the UAV. Interference with the UAV's telemetry and control link is achieved by interfering with signals transmitted from the ground station to the UAV, not signals transmitted from the UAV to the ground station. Interference with satellite navigation links primarily involves interfering with signals transmitted from navigation satellites (GPS, BeiDou, GLONASS, Galileo) to the UAV's navigation receiver.

[0006] Based on the above analysis, when high-end drones entering the drone control area use high-gain directional antennas or even phased array antennas for directional narrow-beam transmission of the telemetry and control link, a single drone control station cannot achieve accurate positioning and effective interference of the drones. Summary of the Invention

[0007] The technical problem to be solved by this invention is that, when high-end UAVs entering the UAV control area use high-gain directional antennas or even phased array antennas for directional narrow beam transmission of the telemetry and control link, a single UAV control station cannot achieve the practical need for accurate positioning and effective interference of UAVs. This invention provides a regional UAV control method and device based on distributed multi-station collaboration, which can achieve accurate positioning and effective interference of high-end UAVs within the control area.

[0008] To address the aforementioned technical problems, a first aspect of this invention discloses a regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration, the method comprising: S1, Obtain regional drone control information; the regional drone control information includes prior information, drone control area, and the number of distributed drone control stations; The prior information includes the equivalent baseband channel fading coefficient of the distributed UAV control station, the equivalent baseband complex signal of the distributed UAV control station, and the equivalent baseband noise of the distributed UAV control station. S2, process the prior information to obtain an estimated value of the UAV position information; the estimated value of the UAV position information includes an estimated value of the direction of the UAV position information and an estimated value of the coordinates of the UAV position information; S3, process the estimated value of the UAV's location information to obtain the regional UAV control result.

[0009] As an optional implementation, in the first aspect of the present invention, processing the prior information to obtain an estimated value of the UAV location information includes: S21, The prior information is processed to obtain the equivalent baseband complex signal received by the antenna element; S22, The equivalent baseband complex signal received by the antenna unit is processed to obtain the direction estimate of the UAV position information; S23, process the equivalent baseband complex signal of the distributed UAV control station to obtain the signal-to-noise ratio of the telemetry and control link signal received by the distributed UAV control station; S24, process the equivalent baseband complex signal of the telemetry and control link received by the distributed UAV control station to obtain the coordinate estimate of the UAV's position information; S25, integrate the direction estimate and the coordinate estimate of the UAV position information to obtain the UAV position information estimate.

[0010] As an optional implementation, in the first aspect of the present invention, processing the prior information to obtain the equivalent baseband complex signal received by the antenna element includes: The prior information is processed using an equivalent baseband complex signal calculation model to obtain the equivalent baseband complex signal received by the antenna element. The equivalent baseband complex signal calculation model expression is as follows: In the formula, For the first The first distributed drone control station The equivalent baseband complex signal received by each antenna element , N represents the number of distributed UAV control stations, and M represents the number of antenna units; for From drones to the first Equivalent baseband channel fading coefficient of a distributed UAV control station yes Equivalent baseband complex signal at time, To transmit the in-phase component of the modulated signal to the telemetry and control link, The quadrature components of the modulated signal are transmitted to the telemetry and control link. It is the spacing between antenna elements. It is the carrier wavelength. , It's the speed of light, the first The angle between the direction of the incoming telemetry and control link signal received by each distributed UAV control station and the normal direction of the antenna array is... , yes Time of the first The first distributed drone control station Equivalent baseband noise of each antenna element.

[0011] As an optional implementation, in the first aspect of the present invention, processing the equivalent baseband complex signal received by the antenna element to obtain a direction estimate of the UAV's position information includes: S221, The equivalent baseband complex signal received by the antenna element is processed to obtain the equivalent baseband complex signal column vector received by the antenna array; S222, The equivalent baseband complex signal column vector received by the antenna array is processed to obtain the vector cross-correlation matrix; S223, The vector cross-correlation matrix is ​​processed to obtain the direction estimate of the UAV's position information.

[0012] As an optional implementation, in the first aspect of the present invention, processing the equivalent baseband complex signal received by the antenna element to obtain the equivalent baseband complex signal column vector received by the antenna array includes: Using the calculation model of the equivalent baseband complex signal column vector received by the antenna array, the equivalent baseband complex signal received by the antenna element is processed to obtain the equivalent baseband complex signal column vector received by the antenna array. The equivalent baseband complex signal column vector calculation model expression received by the antenna array is as follows: in, , , N represents the number of distributed drone control stations, and M represents the number of antenna elements. .

[0013] As an optional implementation, in the first aspect of the present invention, the processing of the equivalent baseband complex signal column vector received by the antenna array to obtain a vector cross-correlation matrix includes: S2221, Process the equivalent baseband noise of the distributed UAV control station to obtain the first parameter information; The expression for the first parameter information is: In the formula, The first parameter is E, which represents the expected value. yes Time of the first The first distributed drone control station Equivalent baseband noise of each antenna element; S2222, The equivalent baseband complex signal of the distributed UAV control station is processed to obtain the second parameter information; The expression for the second parameter information is: In the formula, This is the second parameter information; S2223, The equivalent baseband channel fading coefficient of the UAV control station is processed to obtain the third parameter information; The expression for the third parameter information is: In the formula, This is the third parameter information. ; S2224, Process the first parameter information, the second parameter information and the third parameter information to obtain a vector cross-correlation matrix; The expression for the vector cross-correlation matrix is: In the formula, Let H be the vector cross-correlation matrix, and H denotes taking the complex conjugate.

[0014] As an optional implementation, in the first aspect of the present invention, processing the equivalent baseband noise of the distributed UAV control station to obtain the signal-to-noise ratio of the telemetry and control link signal received by the distributed UAV control station includes: Using the signal-to-noise ratio (SNR) calculation model of the telemetry and control link signal received by the distributed UAV control station, the equivalent baseband noise of the distributed UAV control station is processed to obtain the SNR of the telemetry and control link signal received by the distributed UAV control station. The signal-to-noise ratio expression of the telemetry and control link signal received by the distributed UAV control station is: , in, For the first The signal-to-noise ratio of the telemetry and control link signals received by each distributed UAV control station , , , , yes Time of the first The first distributed drone control station The equivalent baseband noise of each antenna element, for From drones to the first Equivalent baseband channel fading coefficient of a distributed UAV control station yes Equivalent baseband complex signal at time, To transmit the in-phase component of the modulated signal to the telemetry and control link, The quadrature components of the modulated signal are sent to the telemetry and control link.

[0015] A second aspect of this invention discloses a regional unmanned aerial vehicle (UAV) control device based on distributed multi-station collaboration, the device comprising: The information acquisition module is used to acquire regional drone control information; the regional drone control information includes prior information, drone control areas, and the number of distributed drone control stations. The prior information includes the equivalent baseband channel fading coefficient of the distributed UAV control station, the equivalent baseband complex signal of the distributed UAV control station, and the equivalent baseband noise of the distributed UAV control station. The UAV position information estimation module is used to process the prior information to obtain the UAV position information estimation value; the UAV position information estimation value includes the direction estimation value and the coordinate estimation value of the UAV position information. The regional drone control module is used to process the estimated location information of the drones to obtain the regional drone control results.

[0016] As an optional implementation, in the second aspect of the present invention, processing the prior information to obtain an estimated UAV location information includes: S21, The prior information is processed to obtain the equivalent baseband complex signal received by the antenna element; S22, The equivalent baseband complex signal received by the antenna unit is processed to obtain the direction estimate of the UAV position information; S23, process the equivalent baseband complex signal of the distributed UAV control station to obtain the signal-to-noise ratio of the telemetry and control link signal received by the distributed UAV control station; S24, process the equivalent baseband complex signal of the telemetry and control link received by the distributed UAV control station to obtain the coordinate estimate of the UAV's position information; S25, integrate the direction estimate and the coordinate estimate of the UAV position information to obtain the UAV position information estimate.

[0017] As an optional implementation, in the second aspect of the present invention, processing the prior information to obtain the equivalent baseband complex signal received by the antenna element includes: The prior information is processed using an equivalent baseband complex signal calculation model to obtain the equivalent baseband complex signal received by the antenna element. The equivalent baseband complex signal calculation model expression is as follows: In the formula, For the first The first distributed drone control station The equivalent baseband complex signal received by each antenna element , N represents the number of distributed UAV control stations, and M represents the number of antenna units; for From drones to the first Equivalent baseband channel fading coefficient of a distributed UAV control station yes Equivalent baseband complex signal at time, To transmit the in-phase component of the modulated signal to the telemetry and control link, The quadrature components of the modulated signal are transmitted to the telemetry and control link. It is the spacing between antenna elements. It is the carrier wavelength. , It's the speed of light, the first The angle between the direction of the incoming telemetry and control link signal received by each distributed UAV control station and the normal direction of the antenna array is... , yes Time of the first The first distributed drone control station Equivalent baseband noise of each antenna element.

[0018] As an optional implementation, in the second aspect of the present invention, processing the equivalent baseband complex signal received by the antenna element to obtain a direction estimate of the UAV's position information includes: S221, The equivalent baseband complex signal received by the antenna element is processed to obtain the equivalent baseband complex signal column vector received by the antenna array; S222, The equivalent baseband complex signal column vector received by the antenna array is processed to obtain the vector cross-correlation matrix; S223, The vector cross-correlation matrix is ​​processed to obtain the direction estimate of the UAV's position information.

[0019] As an optional implementation, in the second aspect of the present invention, processing the equivalent baseband complex signal received by the antenna element to obtain the equivalent baseband complex signal column vector received by the antenna array includes: Using the calculation model of the equivalent baseband complex signal column vector received by the antenna array, the equivalent baseband complex signal received by the antenna element is processed to obtain the equivalent baseband complex signal column vector received by the antenna array. The equivalent baseband complex signal column vector calculation model expression received by the antenna array is as follows: in, , , N represents the number of distributed drone control stations, and M represents the number of antenna elements. .

[0020] As an optional implementation, in the second aspect of the present invention, the processing of the equivalent baseband complex signal column vector received by the antenna array to obtain a vector cross-correlation matrix includes: S2221, Process the equivalent baseband noise of the distributed UAV control station to obtain the first parameter information; The expression for the first parameter information is: In the formula, The first parameter is E, which represents the expected value. yes Time of the first The first distributed drone control station Equivalent baseband noise of each antenna element; S2222, The equivalent baseband complex signal of the distributed UAV control station is processed to obtain the second parameter information; The expression for the second parameter information is: In the formula, This is the second parameter information; S2223, The equivalent baseband channel fading coefficient of the UAV control station is processed to obtain the third parameter information; The expression for the third parameter information is: In the formula, This is the third parameter information. ; S2224, Process the first parameter information, the second parameter information and the third parameter information to obtain a vector cross-correlation matrix; The expression for the vector cross-correlation matrix is: In the formula, Let H be the vector cross-correlation matrix, and H denotes taking the complex conjugate.

[0021] As an optional implementation, in the second aspect of the present invention, processing the equivalent baseband noise of the distributed UAV control station to obtain the signal-to-noise ratio of the telemetry and control link signal received by the distributed UAV control station includes: Using the signal-to-noise ratio (SNR) calculation model of the telemetry and control link signal received by the distributed UAV control station, the equivalent baseband noise of the distributed UAV control station is processed to obtain the SNR of the telemetry and control link signal received by the distributed UAV control station. The signal-to-noise ratio expression of the telemetry and control link signal received by the distributed UAV control station is: , in, For the first The signal-to-noise ratio of the telemetry and control link signals received by each distributed UAV control station , , , , yes Time of the first The first distributed drone control station The equivalent baseband noise of each antenna element, for From drones to the first Equivalent baseband channel fading coefficient of a distributed UAV control station yes Equivalent baseband complex signal at time, To transmit the in-phase component of the modulated signal to the telemetry and control link, The quadrature components of the modulated signal are sent to the telemetry and control link.

[0022] A third aspect of this invention discloses another regional unmanned aerial vehicle (UAV) control device based on distributed multi-station collaboration, the device comprising: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute some or all of the steps in the regional unmanned aerial vehicle (UAV) prevention and control method based on distributed multi-station collaboration disclosed in the first aspect of the present invention.

[0023] The fourth aspect of the present invention discloses a computer-storable medium storing computer instructions, which, when invoked, are used to execute some or all of the steps in the regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration disclosed in the first aspect of the present invention.

[0024] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: This invention realizes a regional drone control method based on distributed multi-station collaboration. The distributed drone control station deploys multiple drone control stations in the controlled area, so that the signals emitted by drones entering the controlled area will always be received by some drone control stations. Then, through collaborative positioning, the coordinate information or direction information of the drone's position can be obtained. Based on the drone's position information, the multi-station collaborative transmission of interference signals can effectively interfere with the telemetry and control link and the satellite navigation link, so as to achieve the purpose of countering illegal drones in the controlled area. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart illustrating a regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration disclosed in an embodiment of the present invention. Figure 2 This is a schematic diagram of the unmanned aerial vehicle (UAV) control station located between the UAV and the ground control station, as disclosed in an embodiment of the present invention. Figure 3 This is a schematic diagram of the UAV control station located within the extended coverage area of ​​the UAV beam, as disclosed in an embodiment of the present invention; Figure 4 This is a schematic diagram of a drone control station located outside the coverage area of ​​the drone's main beam, as disclosed in an embodiment of the present invention. Figure 5 This is a schematic diagram showing the deployment locations of distributed prevention and control stations within the prevention and control area as disclosed in an embodiment of the present invention; Figure 6 This is a schematic diagram of the efficient working scenario of a centralized UAV control station disclosed in an embodiment of the present invention; Figure 7 This is a schematic diagram of an inefficient working scenario of a centralized UAV control station disclosed in an embodiment of the present invention; Figure 8 This is a schematic diagram of an ineffective working scenario of a centralized UAV control station disclosed in an embodiment of the present invention; Figure 9 This is a schematic diagram of the antenna array of the UAV control station receiving telemetry and control link signals disclosed in an embodiment of the present invention; Figure 10 This is a schematic diagram of determining UAV coordinates by the intersection of directional angles, as disclosed in an embodiment of the present invention; Figure 11 This is a schematic diagram of determining the direction of a UAV by azimuth angle, as disclosed in an embodiment of the present invention; Figure 12 This is a schematic diagram of the structure of a regional unmanned aerial vehicle (UAV) control device based on distributed multi-station collaboration disclosed in an embodiment of the present invention; Figure 13 This is a schematic diagram of another regional unmanned aerial vehicle (UAV) control device based on distributed multi-station collaboration disclosed in an embodiment of the present invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0029] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0030] In all embodiments of the present invention, the variables involved in all computational expressions or mathematical functions are dimensionless before calculation. The values ​​of the independent variables in all computational expressions or mathematical functions in these embodiments conform to the reasonable requirements of the input range of the computational expression or mathematical function, ensuring that the computational expression or mathematical function can be calculated smoothly without violating physical laws or mathematical rules.

[0031] This invention discloses a regional drone control method and apparatus based on distributed multi-station collaboration. The method includes: acquiring regional drone control information; the regional drone control information includes prior information, drone control area, and the number of distributed drone control stations; the prior information includes the equivalent baseband channel fading coefficient of the distributed drone control stations, the equivalent baseband complex signal of the distributed drone control stations, and the equivalent baseband noise of the distributed drone control stations; processing the prior information to obtain estimated drone position information; the estimated drone position information includes the direction estimate and the coordinate estimate of the drone position information; and processing the estimated drone position information to obtain the regional drone control result. This invention utilizes distributed drone control stations to achieve the purpose of countering illegal drones in the controlled area by deploying multiple drone control stations. Detailed descriptions follow.

[0032] Example 1 Please see Figure 1 , Figure 1 This is a flowchart illustrating a regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration disclosed in an embodiment of the present invention. Figure 1 The described regional drone control method based on distributed multi-station collaboration is applied in the field of drone control technology, including location detection and countermeasures against illegal drones within the controlled area. This invention does not limit the scope of the embodiments. Figure 1 As shown, the regional drone control method based on distributed multi-station collaboration can include the following operations: S1, Obtain regional drone control information; the regional drone control information includes prior information, drone control area, and the number of distributed drone control stations; The prior information includes the equivalent baseband channel fading coefficient of the distributed UAV control station, the equivalent baseband complex signal of the distributed UAV control station, and the equivalent baseband noise of the distributed UAV control station. S2, process the prior information to obtain an estimated value of the UAV position information; the estimated value of the UAV position information includes an estimated value of the direction of the UAV position information and an estimated value of the coordinates of the UAV position information; S3, process the estimated value of the UAV's location information to obtain the regional UAV control result.

[0033] Optionally, processing the prior information to obtain the estimated UAV location information includes: S21, The prior information is processed to obtain the equivalent baseband complex signal received by the antenna element; S22, The equivalent baseband complex signal received by the antenna unit is processed to obtain the direction estimate of the UAV position information; S23, process the equivalent baseband complex signal of the distributed UAV control station to obtain the signal-to-noise ratio of the telemetry and control link signal received by the distributed UAV control station; S24, process the equivalent baseband complex signal of the telemetry and control link received by the distributed UAV control station to obtain the coordinate estimate of the UAV's position information; S25, integrate the direction estimate and the coordinate estimate of the UAV position information to obtain the UAV position information estimate.

[0034] Optionally, processing the prior information to obtain the equivalent baseband complex signal received by the antenna element includes: The prior information is processed using an equivalent baseband complex signal calculation model to obtain the equivalent baseband complex signal received by the antenna element. The equivalent baseband complex signal calculation model expression is as follows: In the formula, For the first The first distributed drone control station The equivalent baseband complex signal received by each antenna element , N represents the number of distributed UAV control stations, and M represents the number of antenna units; for From drones to the first Equivalent baseband channel fading coefficient of a distributed UAV control station yes Equivalent baseband complex signal at time, To transmit the in-phase component of the modulated signal to the telemetry and control link, The quadrature components of the modulated signal are transmitted to the telemetry and control link. It is the spacing between antenna elements. It is the carrier wavelength. , It's the speed of light, the first The angle between the direction of the incoming telemetry and control link signal received by each distributed UAV control station and the normal direction of the antenna array is... , yes Time of the first The first distributed drone control station Equivalent baseband noise of each antenna element.

[0035] Optionally, processing the equivalent baseband complex signal received by the antenna element to obtain the direction estimate of the UAV's position information includes: S221, The equivalent baseband complex signal received by the antenna element is processed to obtain the equivalent baseband complex signal column vector received by the antenna array; S222, The equivalent baseband complex signal column vector received by the antenna array is processed to obtain the vector cross-correlation matrix; S223, The vector cross-correlation matrix is ​​processed to obtain the direction estimate of the UAV's position information.

[0036] Optionally, the step of processing the equivalent baseband complex signal received by the antenna element to obtain the equivalent baseband complex signal column vector received by the antenna array includes: Using the calculation model of the equivalent baseband complex signal column vector received by the antenna array, the equivalent baseband complex signal received by the antenna element is processed to obtain the equivalent baseband complex signal column vector received by the antenna array. The equivalent baseband complex signal column vector calculation model expression received by the antenna array is as follows: in, , , N represents the number of distributed drone control stations, and M represents the number of antenna elements. .

[0037] Optionally, the processing of the equivalent baseband complex signal column vector received by the antenna array to obtain the vector cross-correlation matrix includes: S2221, Process the equivalent baseband noise of the distributed UAV control station to obtain the first parameter information; The expression for the first parameter information is: In the formula, The first parameter is E, which represents the expected value. yes Time of the first The first distributed drone control station Equivalent baseband noise of each antenna element; S2222, The equivalent baseband complex signal of the distributed UAV control station is processed to obtain the second parameter information; The expression for the second parameter information is: In the formula, This is the second parameter information; S2223, The equivalent baseband channel fading coefficient of the UAV control station is processed to obtain the third parameter information; The expression for the third parameter information is: In the formula, This is the third parameter information. ; S2224, Process the first parameter information, the second parameter information and the third parameter information to obtain a vector cross-correlation matrix; The expression for the vector cross-correlation matrix is: In the formula, Let H be the vector cross-correlation matrix, and H denotes taking the complex conjugate.

[0038] Optionally, the step of processing the equivalent baseband noise of the distributed UAV control station to obtain the signal-to-noise ratio of the telemetry and control link signal received by the distributed UAV control station includes: Using the signal-to-noise ratio (SNR) calculation model of the telemetry and control link signal received by the distributed UAV control station, the equivalent baseband noise of the distributed UAV control station is processed to obtain the SNR of the telemetry and control link signal received by the distributed UAV control station. The signal-to-noise ratio expression of the telemetry and control link signal received by the distributed UAV control station is: , in, For the first The signal-to-noise ratio of the telemetry and control link signals received by each distributed UAV control station , , , , yes Time of the first The first distributed drone control station The equivalent baseband noise of each antenna element, for From drones to the first Equivalent baseband channel fading coefficient of a distributed UAV control station yes Equivalent baseband complex signal at time, To transmit the in-phase component of the modulated signal to the telemetry and control link, The quadrature components of the modulated signal are sent to the telemetry and control link.

[0039] Assume the signal-to-noise ratio threshold of the direction-finding algorithm is set to... If Signal-to-noise ratio of a distributed drone control station Then, based on the ranking, the intersection point of the drone's heading angle measured by the two drone control stations with the highest signal-to-noise ratio is selected as the coordinate estimate of the drone's position information, such as... Figure 10 As shown. From Figure 10 As can be seen, the signal-to-noise ratio (SNR) of the distributed drone control stations is ranked as follows: B has the highest SNR, followed by C, and then A has the lowest. The coordinates where the azimuth angles measured by B and C intersect are the intersection of the two red dashed lines. This shows that the positioning coordinates are relatively accurate relative to the drone's true position. If the two highest-ranked azimuth angles are not selected, and instead the coordinates where the azimuth angles measured by B and A intersect (the intersection of the red and green dashed lines) are chosen as the estimated drone position coordinates, the deviation will be significant, making subsequent interference with the drone much more difficult. If there is a distributed drone control station with a SNR... Therefore, only the direction information of the UAV can be obtained, not its coordinate information. The next step, interfering with the UAV's telemetry and control link and navigation link, will be carried out by the UAV control station that meets the signal-to-noise ratio requirements, such as... Figure 11 As shown.

[0040] from Figure 11 As can be seen from the data, only the signal-to-noise ratio of distributed drone control stations A meets the requirements, and its direction is represented by a red dashed line. The drone is basically in this direction. The signal-to-noise ratios of distributed drone control stations B and C do not meet the requirements, and their azimuth angles are represented by green dashed lines. The intersection of their azimuth angles with the azimuth angle of A is far from the drone's true coordinates, making it impossible to effectively determine the drone's position. Subsequent interference with the drone cannot be based on the intersection coordinates and can only be carried out based on the azimuth angle of A and implemented by distributed drone control station A.

[0041] After determining the coordinates or direction of the UAV's location through the above steps, it is necessary to interfere with the UAV's telemetry and control link and satellite navigation link. If the UAV's coordinates are obtained, the signal-to-noise ratio of the distributed UAV control station should be selected. A collection of drone control stations (Note: signal-to-noise ratio threshold here) It determines which drone control stations are involved in interfering with drones based on the channel fading state, using the aforementioned signal-to-noise ratio threshold. (used to determine which drone control stations' directional information can be used to measure drone position), assuming a distributed drone control station system. In the set, its first... The telemetry and control link interference signal transmitted by each antenna element is in, It is interference power. and It is a normalized in-phase and quadrature interference signal that satisfies and Its waveform is a random signal, and its bandwidth covers the bandwidth of the measurement and control link. For the center frequency of the telemetry and control link, Distributed drone control station The drone's orientation angle is calculated based on its estimated location information, with itself as the reference point.

[0042] The interference signals to satellite navigation links are similar to those in the above formula, except that: and Bandwidth coverage for satellite navigation link bandwidth, This is the center frequency of the satellite navigation link.

[0043] If only the directional information of the drone's location is available, assuming the required distributed drone control station number is also... The interference to the telemetry, tracking, and command (TT&C) link and satellite navigation link is similar to the above formula, except that the direction and angle information is... This refers to the direction and angle information of the drone estimated by the distributed drone control station based on the received telemetry and control link signals.

[0044] As can be seen, this invention realizes a regional drone control method based on distributed multi-station collaboration. The distributed drone control station deploys multiple drone control stations in the controlled area, so that the signals emitted by drones entering the controlled area will always be received by some drone control stations. Then, through collaborative positioning, the coordinate information or direction information of the drone's position can be obtained. Based on the drone's position information, the multi-station collaborative transmission of interference signals can effectively interfere with the telemetry and control link and the satellite navigation link, thereby achieving the purpose of countering illegal drones in the controlled area.

[0045] Example 2 High-end drones and ground control stations are equipped with high-gain directional antennas or even phased array antennas. The telemetry and control link between them uses directional narrow-beam transmission to improve link gain and received signal quality. If the drone control station is within the narrow-beam coverage area between the drone and the ground control station, it can effectively perform target localization and jamming. Figure 2 and Figure 3 As shown. In Figure 2In this system, the UAV control station is located between the UAV and the ground station. The UAV transmits signals that enter the control station along its main lobe (the direction of strongest signal). The control station can effectively locate the UAV using direction-finding algorithms, and then transmits jamming signals along the UAV's main lobe direction to effectively interfere with the UAV's telemetry and control link receiver. However, since the main lobe of the satellite navigation link signal faces space, the jamming effect of the UAV control station's jamming signal entering the satellite navigation link receiver from different directions is not significantly different. Figure 3 In this scenario, the UAV control station is located within the extended coverage area of ​​the UAV's beam. The UAV's transmitted signal enters the control station along its main lobe. The control station can effectively locate the UAV using direction-finding algorithms, and then transmit jamming signals along the UAV's main lobe direction to effectively interfere with the UAV's telemetry and control link receiver. If the control station is located outside the main beam coverage area between the UAV and the ground control station, then the control station cannot effectively locate and jam the target. Figure 4 As shown. In Figure 4 In this scenario, the UAV transmits a signal that enters the UAV control station along the back lobe (the direction of least signal strength). Due to the weak signal, it is highly unlikely to reach the receiver's sensitivity, making effective signal reception impossible. Even if the sensitivity threshold is exceeded, the low signal-to-noise ratio will affect the accuracy of the direction-finding algorithm, preventing accurate determination of the UAV's position. During the interference phase, even with prior information about the UAV's position, the interference effect achieved by the interference signal transmitted by the UAV control station along the back lobe direction is very limited. Due to the attenuation effect of the back lobe on the interference signal, effectively blocking the telemetry and control link signal requires transmitting an interference signal with extremely high power, which places high demands on the power amplifier and RF link capabilities of the UAV control station, making it difficult to achieve. Even if achieved, it would cause significant spectrum pollution in the electromagnetic field over a wide area, subject to policy constraints. Furthermore, since accurate information about the UAV's position is not available in practice, the main lobe of the satellite navigation link interference signal transmitted by the UAV control station is not aligned with the UAV, weakening the interference signal strength entering the UAV's satellite navigation link and reducing the interference radius.

[0046] Note: Direction finding and positioning of a UAV is achieved by transmitting signals from the UAV to the ground station, not the other way around. Interference with the UAV's telemetry and control link is achieved by interfering with signals transmitted from the ground station to the UAV, not the other way around. Interference with the satellite navigation link primarily involves interfering with signals transmitted from navigation satellites (GPS, BeiDou, GLONASS, Galileo) to the UAV's navigation receiver.

[0047] Based on the above analysis, when high-end drones entering the drone control area use high-gain directional antennas or even phased array antennas for directional narrow-beam transmission of the telemetry and control link, a single drone control station cannot achieve accurate positioning and effective interference. To address this practical need, this patent proposes a regional drone control technology and method based on the collaboration of multiple distributed drone control stations, which can achieve accurate positioning and effective interference of high-end drones within the control area.

[0048] When high-end drones entering the drone control area use high-gain directional antennas or even phased array antennas for directional narrow-beam transmission of the telemetry and control link, multiple distributed drone control stations are deployed in the control area to work together to accurately locate and effectively interfere with high-end drones in the control area.

[0049] The technical solution adopted in this invention is as follows: Figure 5 As shown, the circular area represents the drone control zone. The original single drone control station is referred to here as a centralized drone control station, located at node D. Assume that three distributed drone control stations are deployed, located at nodes A, B, and C respectively. Each distributed drone control station uses a phased array antenna with a horizontal scanning range of 120°, thus achieving 360° coverage without blind spots.

[0050] Step 1: Based on prior information, the antenna arrays of distributed UAV control stations A, B, and C receive the telemetry and control link signals on the UAV telemetry and control link frequency band and then calculate the direction of arrival of the UAV signal using a direction-finding algorithm.

[0051] Step 2: Based on the signal-to-noise ratio (SNR) of the telemetry and control link signals received by the three distributed UAV control stations, and provided that the SNR threshold is met, select the intersection point of the radio wave directions calculated by the two distributed UAV control stations with the strongest SNR as the coordinate estimate of the UAV's position information; if only one UAV control station receives a telemetry and control link signal with an SNR that meets the requirements, then only output the UAV's direction information with that control station as the base point as the direction estimate of the UAV's position information.

[0052] Step 3: If the coordinates of the UAV's location information are available, the three distributed UAV control stations will align the receiving beams of their antenna arrays with the UAV's location. Based on the signal-to-noise ratio of the signal received on the telemetry and control link frequency band, they will determine whether the signal exceeds a preset threshold as a channel quality assessment.

[0053] Step 4: If the coordinates of the UAV's location information are estimated, the distributed UAV control station that receives a signal-to-noise ratio exceeding a preset threshold on the telemetry and control link frequency band will transmit an interference signal on the telemetry and control link frequency band, with the signal transmission direction aligned with the estimated UAV position; if the direction of the UAV's location information is estimated, the control station that serves as the direction reference point will transmit an interference signal on the telemetry and control link frequency band, with the signal transmission direction aligned with the UAV's direction.

[0054] Step 5: If the coordinates of the UAV's location information are estimated, the distributed UAV control station transmits an interference signal on the satellite navigation frequency band, with the signal transmission direction aligned with the estimated UAV location; if the direction of the UAV's location information is estimated, the control station, which serves as the direction reference point, transmits an interference signal on the satellite navigation frequency band, with the signal transmission direction aligned with the UAV's direction.

[0055] By dividing the scenarios into efficient, inefficient, and ineffective scenarios for centralized drone control stations, the relative advantages of distributed drone control stations are analyzed.

[0056] like Figure 6 The diagram illustrates an efficient operating scenario for a centralized UAV control station. Centralized UAV control station D and distributed UAV control station B can effectively receive the telemetry and control link signals transmitted by the UAV through its main lobe. Distributed UAV control station C receives relatively lower quality signals, while distributed UAV control station A receives even lower quality signals. Although the centralized UAV control station can effectively interfere with the UAV in this scenario, the distributed UAV control station, through coordinated interference, possesses superior interference performance at the same transmission power.

[0057] like Figure 7 The diagram illustrates an inefficient operating scenario for centralized UAV control stations. Centralized UAV control station D and distributed UAV control station B can only receive telemetry and control (TT&C) link signals transmitted by UAVs through their back lobes (not the weakest signal direction). Distributed UAV control station A receives relatively better quality TT&C link signals, while distributed UAV control station C receives even better signals. In this scenario, centralized UAV control station D struggles to accurately obtain the UAV's directional information needed to interfere with the UAV, and effective interference requires extremely high power, resulting in very low efficiency. Distributed UAV control stations, through the collaborative work of nodes A and C, can obtain more accurate UAV position information. Collaborative interference from nodes A and C can effectively disrupt the UAV's TT&C link, while collaborative work from nodes A, B, and C can effectively disrupt the UAV's satellite navigation link.

[0058] like Figure 8As shown, this illustrates a scenario where a centralized UAV control station is ineffective. Centralized UAV control station D can only receive telemetry and control (TT&C) link signals transmitted by UAVs through the back lobe (almost the weakest signal direction). Distributed UAV control station A receives TT&C link signals transmitted from the main lobe, which are of very high quality. Even if the TT&C link signals received by distributed UAV control stations B and C are of poor quality (received signals are closer to the back lobe), failing to meet the signal-to-noise ratio threshold and thus unable to determine direction using direction-finding algorithms, UAV control station A can still accurately determine the UAV's direction and effectively interfere with the TT&C link and satellite navigation link.

[0059] Example 3 Assuming the drone control area is a circular region (the control area is usually irregular in shape, and the circular region is the circle with the smallest radius covering the irregular shape), if the number of distributed drone control stations is... N A distributed drone control station is deployed every 360° / N angles on a circle. By adjusting the phase control beam scanning range of the antenna array of the distributed drone control station, the beam scanning range of each distributed drone control station is controlled within the normal direction of the antenna array. Within the range.

[0060] Assuming the distributed UAV control station possesses prior information on the frequency points and waveforms of the UAV telemetry and control link, and the antenna array of the distributed UAV control station has an array element count of... A horizontal linear array (expandable to a two-dimensional array as needed), the first The first antenna unit of the distributed drone control station, after completing the telemetry and control link synchronization, The signal received at any time is (1) in, and These are the in-phase and quadrature components of the modulation signal transmitted by the telemetry and control link, respectively. and These are the modulated signals acting on the drone and the... The wireless channel of a distributed UAV control station has in-phase and quadrature components, the telemetry and control link is a narrowband signal, and the center frequency is [missing information]. , yes Time of the first The noise signal received by the first antenna unit of a distributed UAV control station. After down-conversion and baseband filtering, the equivalent baseband complex signal is: (2) in, yes From drones to the first Equivalent baseband channel fading coefficient of a distributed UAV control station yes Equivalent baseband complex signal at time, yes Time of the first Equivalent baseband noise of the first antenna unit of a distributed unmanned aerial vehicle (UAV) control station.

[0061] According to antenna array theory, the first The first distributed drone control station The equivalent baseband complex signal received by each antenna element is (3) in, It is the spacing between antenna elements. It is the carrier wavelength ( , (It is the speed of light), the first The angle between the direction of the incoming telemetry and control link signal received by each distributed UAV control station and the normal direction of the antenna array is... , yes Time of the first The first distributed drone control station The equivalent baseband noise of each antenna element, such as Figure 9 As shown.

[0062] Assumption , , The equivalent baseband complex signal column vector received by the antenna array is (4) The vector cross-correlation matrix is (5) Using the cross-correlation matrix as input, and employing direction-finding algorithms (such as the MUSIC algorithm and the ESPRIT algorithm), the first... The estimated drone direction value from a distributed drone control station .

[0063] Definition of the first The signal-to-noise ratio of the telemetry and control link signals received by the distributed drone control stations is: Assuming the signal-to-noise ratio threshold of the direction-finding algorithm is set to... If Signal-to-noise ratio of a distributed drone control station Then, based on the ranking, the intersection point of the drone's heading angle measured by the two drone control stations with the highest signal-to-noise ratio is selected as the coordinate estimate of the drone's position information, such as... Figure 10 As shown.

[0064] from Figure 10 As can be seen, the signal-to-noise ratio (SNR) of the distributed drone control stations is ranked as follows: B has the highest SNR, followed by C, and then A has the lowest. The coordinates where the azimuth angles measured by B and C intersect are the intersection of the two red dashed lines. This shows that the positioning coordinates are relatively accurate relative to the drone's true position. If the two highest-ranked azimuth angles were not selected, and instead the coordinates where the azimuth angles measured by B and A intersect (the intersection of the red and green dashed lines) were chosen as the estimated drone position coordinates, the deviation would be significant, making subsequent interference with the drone much more difficult.

[0065] If there is a signal-to-noise ratio of a distributed drone control station Therefore, only the direction information of the UAV can be obtained, not its coordinate information. The next step, interfering with the UAV's telemetry and control link and navigation link, will be carried out by the UAV control station that meets the signal-to-noise ratio requirements, such as... Figure 11 As shown.

[0066] from Figure 11 As can be seen from the data, only the signal-to-noise ratio of distributed drone control stations A meets the requirements, and its direction is represented by a red dashed line. The drone is basically in this direction. The signal-to-noise ratios of distributed drone control stations B and C do not meet the requirements, and their azimuth angles are represented by green dashed lines. The intersection of their azimuth angles with the azimuth angle of A is far from the drone's true coordinates, making it impossible to effectively determine the drone's position. Subsequent interference with the drone cannot be based on the intersection coordinates and can only be carried out based on the azimuth angle of A and implemented by distributed drone control station A.

[0067] After determining the coordinates or direction of the UAV's location through the above steps, it is necessary to interfere with the UAV's telemetry and control link and satellite navigation link.

[0068] If the coordinates of the drone's location are obtained, the signal-to-noise ratio of the distributed drone control station should be selected. A collection of drone control stations (Note: signal-to-noise ratio threshold here) It determines which drone control stations are involved in interfering with drones based on the channel fading state, using the aforementioned signal-to-noise ratio threshold. (used to determine which drone control stations' directional information can be used to measure drone position), assuming a distributed drone control station system. In the set, its first... The telemetry and control link interference signal transmitted by each antenna element is (6) in, It is interference power. and It is a normalized in-phase and quadrature interference signal that satisfies and Its waveform is a random signal, and its bandwidth covers the bandwidth of the measurement and control link. For the center frequency of the telemetry and control link, Distributed drone control station The drone's orientation angle is calculated based on its estimated location information, with itself as the reference point.

[0069] The interference signal to the satellite navigation link is similar to that in equation (6), except that: and Bandwidth coverage for satellite navigation link bandwidth, This is the center frequency of the satellite navigation link.

[0070] If only the directional information of the drone's location is available, assuming the required distributed drone control station number is also... The interference to the telemetry and control link and the satellite navigation link is similar to that in equation (6), except that the direction and angle information is... This refers to the direction and angle information of the drone estimated by the distributed drone control station based on the received telemetry and control link signals.

[0071] High-end drones and ground control stations are equipped with high-gain directional antennas or even phased array antennas. The telemetry and control link between the two uses directional narrow beam transmission. If a single drone control station is used, the drone control station may not be within the effective coverage range of the drone's transmission beam, which would prevent the drone control station from effectively locating the drone and thus from effectively interfering with it.

[0072] Distributed drone control stations deploy multiple drone control stations within a controlled area, ensuring that signals emitted by drones entering the controlled area are always received by some of these stations. Through collaborative positioning, the coordinates or direction information of the drone's location can be obtained. Based on the drone's location information, multi-station collaborative transmission of jamming signals can effectively interfere with the telemetry and control link and satellite navigation link, thereby achieving the goal of countering illegal drones in the controlled area.

[0073] Example 4 Please see Figure 12 , Figure 12 This is a schematic diagram of a regional unmanned aerial vehicle (UAV) control device based on distributed multi-station collaboration, as disclosed in an embodiment of the present invention. Figure 12 The described regional drone control device based on distributed multi-station collaboration is applied in the field of drone control technology, including location detection and countermeasures against illegal drones within the controlled area. This invention does not limit the scope of the embodiments. Figure 12 As shown, the regional drone control device based on distributed multi-station collaboration can include the following operations: S301, Information Acquisition Module, used to acquire regional drone control information; the regional drone control information includes prior information, drone control area, and the number of distributed drone control stations. The prior information includes the equivalent baseband channel fading coefficient of the distributed UAV control station, the equivalent baseband complex signal of the distributed UAV control station, and the equivalent baseband noise of the distributed UAV control station. S302, UAV position information estimation module, used to process the prior information to obtain UAV position information estimation; the UAV position information estimation includes the direction estimation and coordinate estimation of the UAV position information; S303, Regional UAV Prevention and Control Module, is used to process the estimated value of the UAV's location information to obtain the regional UAV prevention and control result.

[0074] Example 5 Please see Figure 13 , Figure 13 This is a schematic diagram of another regional unmanned aerial vehicle (UAV) control device based on distributed multi-station collaboration disclosed in an embodiment of the present invention. Figure 13 The described regional drone control device based on distributed multi-station collaboration is applied in the field of drone control technology, including location detection and countermeasures against illegal drones within the controlled area. This invention does not limit the scope of the embodiments. Figure 13 As shown, the regional drone control device based on distributed multi-station collaboration can include the following operations: Memory 401 storing executable program code; Processor 402 coupled to memory 401; The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the regional UAV prevention and control method based on distributed multi-station collaboration described in Embodiments 1, 2, and 3.

[0075] Example 6 This invention discloses a computer-readable storage medium storing a computer program for electronic data interchange, wherein the computer program enables a computer to execute the steps in the regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration described in Embodiments 1, 2, and 3.

[0076] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0077] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0078] Finally, it should be noted that the regional UAV prevention and control method and device based on distributed multi-station collaboration disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaborative operation, characterized in that, The method includes: S1, Obtain regional drone control information; the regional drone control information includes prior information, drone control area, and the number of distributed drone control stations; The drone control area is a circular region. If the number of distributed drone control stations is N, and one station is deployed every 360° / N angles along the circle, the beam scanning range of each station is controlled by adjusting the phase control beam scanning range of the antenna array. Within the range; The prior information includes the equivalent baseband channel fading coefficient of the distributed UAV control station, the equivalent baseband complex signal of the distributed UAV control station, and the equivalent baseband noise of the distributed UAV control station. S2, process the prior information to obtain an estimated value of the UAV's position information; the estimated value of the UAV's position information includes a direction estimate and a coordinate estimate, including: S21, The prior information is processed to obtain the equivalent baseband complex signal received by the antenna element; S22, The equivalent baseband complex signal received by the antenna unit is processed to obtain the direction estimate of the UAV position information; S23, process the equivalent baseband noise of the distributed UAV control station to obtain the signal-to-noise ratio of the telemetry and control link signal received by the distributed UAV control station; S24, process the equivalent baseband complex signal of the telemetry and control link received by the distributed UAV control station to obtain the coordinate estimate of the UAV's position information; Assume the signal-to-noise ratio threshold of the direction-finding algorithm is set to... If Signal-to-noise ratio of a distributed drone control station Based on the ranking, the intersection point of the drone's heading angle measured by the two drone control stations with the highest signal-to-noise ratio is selected as the coordinate estimate of the drone's position information; if there is one distributed drone control station with a signal-to-noise ratio of... It can only obtain the direction information of the UAV, but cannot obtain the coordinate information of the UAV. The next step of interfering with the UAV telemetry and control link and the navigation link will be carried out by the UAV control station that meets the signal-to-noise ratio requirements. S25, integrate the direction estimate and the coordinate estimate of the UAV position information to obtain the UAV position information estimate; S3, process the estimated value of the UAV's location information to obtain the regional UAV control result; After determining the coordinates or direction of the UAV's location, it is necessary to interfere with the UAV's telemetry and control link and satellite navigation link; if the coordinates of the UAV's location are obtained, the signal-to-noise ratio of the distributed UAV control station should be selected. A collection of drone control stations, signal-to-noise ratio threshold It determines which drone control stations are involved in interfering with drones based on the channel fading state, and the signal-to-noise ratio threshold. To determine which drone control stations' directional information can be used to measure drone location, assuming a distributed drone control station system... In the set, its first... The telemetry and control link interference signal transmitted by each antenna element is in, It is interference power. and It is a normalized in-phase and quadrature interference signal that satisfies and Its waveform is a random signal, and its bandwidth covers the bandwidth of the telemetry and control link. For the center frequency of the telemetry and control link, Distributed drone control station The drone's orientation angle is calculated based on its estimated location information, with itself as the reference point. If the coordinates of the UAV's location information are estimated, the distributed UAV control station that receives a signal with a signal-to-noise ratio exceeding a preset threshold on the telemetry and control link frequency band will transmit an interference signal on the telemetry and control link frequency band, with the signal transmission direction aligned with the estimated UAV position; if the direction of the UAV's location information is estimated, the control station that serves as the direction reference point will transmit an interference signal on the telemetry and control link frequency band, with the signal transmission direction aligned with the UAV's direction. If the coordinates of the UAV's location are estimated, the distributed UAV control station transmits jamming signals on the satellite navigation frequency band, with the signal transmission direction aligned with the estimated UAV location; if the direction of the UAV's location is estimated, the control station, which serves as the direction reference point, transmits jamming signals on the satellite navigation frequency band, with the signal transmission direction aligned with the UAV's direction.

2. The regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration according to claim 1, characterized in that, The process of processing the prior information to obtain the equivalent baseband complex signal received by the antenna element includes: The prior information is processed using an equivalent baseband complex signal calculation model to obtain the equivalent baseband complex signal received by the antenna element. The equivalent baseband complex signal calculation model expression is as follows: In the formula, For the first The first distributed drone control station The equivalent baseband complex signal received by each antenna element , N represents the number of distributed UAV control stations, and M represents the number of antenna units; for From drones to the first Equivalent baseband channel fading coefficient of a distributed UAV control station yes Equivalent baseband complex signal at time, To transmit the in-phase component of the modulated signal to the telemetry and control link, The quadrature components of the modulated signal are transmitted to the telemetry and control link. It is the spacing between antenna elements. It is the carrier wavelength. , It's the speed of light, the first The angle between the direction of the incoming telemetry and control link signal received by each distributed UAV control station and the normal direction of the antenna array is... , yes Time of the first The first distributed drone control station The equivalent baseband noise of each antenna element, with a center frequency of [missing value]. .

3. The regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration according to claim 1, characterized in that, The process of processing the equivalent baseband complex signal received by the antenna element to obtain the direction estimate of the UAV's position information includes: S221, The equivalent baseband complex signal received by the antenna element is processed to obtain the equivalent baseband complex signal column vector received by the antenna array; S222, The equivalent baseband complex signal column vector received by the antenna array is processed to obtain the vector cross-correlation matrix; S223, The vector cross-correlation matrix is ​​processed to obtain the direction estimate of the UAV's position information.

4. The regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration according to claim 3, characterized in that, The process of processing the equivalent baseband complex signal received by the antenna element to obtain the equivalent baseband complex signal column vector received by the antenna array includes: Using the calculation model of the equivalent baseband complex signal column vector received by the antenna array, the equivalent baseband complex signal received by the antenna element is processed to obtain the equivalent baseband complex signal column vector received by the antenna array. The equivalent baseband complex signal column vector calculation model expression received by the antenna array is as follows: in, For the first The first distributed drone control station The equivalent baseband complex signal received by each antenna element , N represents the number of distributed drone control stations, and M represents the number of antenna elements. yes Equivalent baseband complex signal at time, To transmit the in-phase component of the modulated signal to the telemetry and control link, The quadrature components of the modulated signal are sent to the telemetry and control link.

5. The regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration according to claim 3, characterized in that, The process of processing the equivalent baseband complex signal column vector received by the antenna array to obtain the vector cross-correlation matrix includes: S2221, Process the equivalent baseband noise of the distributed UAV control station to obtain the first parameter information; The expression for the first parameter information is: In the formula, The first parameter is E, which represents the expected value. yes Time of the first The first distributed drone control station Equivalent baseband noise of each antenna element; S2222, The equivalent baseband complex signal of the distributed UAV control station is processed to obtain the second parameter information; The expression for the second parameter information is: In the formula, This is the second parameter information; S2223, The equivalent baseband channel fading coefficient of the UAV control station is processed to obtain the third parameter information; The expression for the third parameter information is: In the formula, This is the third parameter information. ; S2224, Process the first parameter information, the second parameter information and the third parameter information to obtain a vector cross-correlation matrix; The expression for the vector cross-correlation matrix is: In the formula, Let H be the vector cross-correlation matrix, and H denotes taking the complex conjugate.

6. The regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration according to claim 1, characterized in that, The process of processing the equivalent baseband noise of the distributed UAV control station to obtain the signal-to-noise ratio of the telemetry and control link signal received by the distributed UAV control station includes: Using the signal-to-noise ratio (SNR) calculation model of the telemetry and control link signal received by the distributed UAV control station, the equivalent baseband noise of the distributed UAV control station is processed to obtain the SNR of the telemetry and control link signal received by the distributed UAV control station. The signal-to-noise ratio expression of the telemetry and control link signal received by the distributed UAV control station is: ， in, For the first The signal-to-noise ratio of the telemetry and control link signals received by each distributed UAV control station , , , , yes Time of the first The first distributed drone control station The equivalent baseband noise of each antenna element, for From drones to the first Equivalent baseband channel fading coefficient of a distributed UAV control station yes Equivalent baseband complex signal at time, To transmit the in-phase component of the modulated signal to the telemetry and control link, The quadrature components of the modulated signal are sent to the telemetry and control link.

7. A regional unmanned aerial vehicle (UAV) control device based on distributed multi-station collaboration, applied to the regional UAV control method based on distributed multi-station collaboration as described in any one of claims 1-6, characterized in that, The device includes: The information acquisition module is used to acquire regional drone control information; the regional drone control information includes prior information, drone control areas, and the number of distributed drone control stations. The prior information includes the equivalent baseband channel fading coefficient of the distributed UAV control station, the equivalent baseband complex signal of the distributed UAV control station, and the equivalent baseband noise of the distributed UAV control station. The UAV position information estimation module is used to process the prior information to obtain the UAV position information estimation value; the UAV position information estimation value includes the direction estimation value and the coordinate estimation value of the UAV position information. The regional drone control module is used to process the estimated location information of the drones to obtain the regional drone control results.

8. A regional unmanned aerial vehicle (UAV) control device based on distributed multi-station collaborative operation, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration as described in any one of claims 1-6.

9. A computer-storable medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the regional unmanned aerial vehicle (UAV) control method based on distributed multi-station collaboration as described in any one of claims 1-6.

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